Microsoft Fabric Consulting Services
End-to-end Fabric optimization, migration, and production analytics and AI.
25+
Years of data expertise
100K+
Workloads migrated or managed
45+
Technology specializations
Pythian handles every workload, migration path, and optimization challenge
Production-ready Microsoft Fabric solutions for every stage of your journey.
Harden for production scale
Performance and capacity optimization
We identify bottlenecks, governance gaps, and cost overruns across your Fabric environment. We design production-grade OneLake architectures with capacity right-sizing and medallion-layer governance to make Fabric enterprise-ready.
Secure and govern your tenant
Purview governance and security architecture
We implement Purview governance—classification, sensitivity labels, lineage, and policy enforcement—with security spanning Entra ID, RBAC, RLS, OLS, and network isolation.
Monitor and optimize 24/7
Ongoing Fabric managed support
24/7 proactive monitoring of capacity, pipelines, Spark performance, Power BI refreshes, and security alerts. We keep your platform at peak efficiency while controlling costs.
Migrate legacy Microsoft workloads
SSIS, Synapse, and ADF migration
We re-engineer SSIS into Fabric-native ELT, migrate Synapse SQL pools with T-SQL remediation, convert ADF pipelines, and transition Power BI Premium to F-SKU capacity—end to end.
Build modern data pipelines
Data engineering and automation
Production pipelines built on medallion architecture with Fabric Pipelines, Spark Notebooks, and Dataflow Gen2. CI/CD with Git integration keeps workflows version-controlled and promotable across environments.
Upskill your team on Fabric
Team enablement
We upskill your teams on Spark, PySpark, lakehouse patterns, and Fabric administration. Practical training grounded in your actual workloads ensures long-term platform ownership.
Deliver self-service analytics
Production analytics and Power BI modernization
We transform legacy SSRS reports into self-service Power BI analytics with DirectLake performance. Consolidated semantic models and governed access let business users get answers without IT bottlenecks.
Build real-time intelligence
Streaming and event-driven analytics
Streaming architectures using real-time intelligence, Eventstreams, and KQL databases for operational monitoring, IoT analytics, and event-driven processing—delivering insights the moment they matter.
Enable production AI
ML, Copilot, and GenAI enablement
We prepare your Fabric data estate for generative AI and predictive analytics—ML models in Fabric notebooks, Copilot enablement, and RAG pipelines grounded in your enterprise data.
Explore Pythian's data consulting services
Unlock significant ROI from your Microsoft Fabric investment.
From data strategy and governance to architecture, migration, and analytics, Pythian's data consultants help you unlock the full value of your Microsoft Fabric investment—with expertise across 45+ technologies and decades of enterprise data experience.
Microsoft Fabric consulting that ensures production-grade platform success
Environment evaluation
We evaluate your current environment—architecture, governance, capacity, and security—and deliver a prioritized roadmap sequenced for the fastest path to business value.
Capacity right-sizing
We design a production-grade OneLake architecture with Purview governance, security, and capacity right-sizing to ensure predictable spend from day one.
Workload migration
We migrate legacy Microsoft workloads into Fabric—SSIS, Synapse, ADF, and Power BI Premium—with dual-run validation to ensure zero disruption.
Readying AI for production
We deliver Power BI dashboards with DirectLake performance, self-service BI, and real-time operational analytics. For AI-ready organizations, we enable Copilot and build ML pipelines grounded in OneLake data.
Around the clock data support
24/7 monitoring and optimization of your Fabric environment, paired with team enablement on Spark, lakehouse patterns, and Fabric administration.
Ready to make Fabric work at enterprise scale?
Pythian's related Microsoft Fabric services
Our end-to-end data services ensure your Fabric investment delivers lasting business value.
Build resilient, modern pipelines
Data engineering consulting
We replace fragmented ETL with resilient, observable pipelines built on medallion architecture with Spark optimization and modern orchestration.
Deliver real-time insights
Production analytics
From legacy SSRS to real-time, self-service Power BI dashboards with DirectLake performance. Business users get answers in seconds, not the hours batch processing typically requires.
Keep your platform running at peak
Managed services
24/7 Fabric monitoring, optimization, and support—handled proactively so your team can focus on building.
Microsoft Fabric consulting services frequently asked questions (FAQ)
Security and governance are built into every phase of our Fabric engagements—not bolted on at the end. We start with a comprehensive assessment of your existing security posture, including Entra ID configuration, network isolation, and data classification. During migration, we implement Microsoft Purview governance from the outset—sensitivity labels, data classification, lineage tracking, and policy enforcement. Access controls are designed using RBAC, row-level security (RLS), and object-level security (OLS) mapped to your organizational roles. Workspace hierarchy and naming conventions are designed to enforce data domain boundaries. For regulated industries, we configure private endpoints, network isolation, and audit logging to meet compliance requirements before any production data moves.
The ROI comes from multiple sources. Infrastructure cost savings are often the most immediate win. Beyond cost reduction, organizations typically see significant improvement in Power BI report render times through DirectLake optimization, dramatic reductions in operational complexity (from managing five or more separate Azure services to a single governed platform), and the ability to enable self-service analytics and production AI capabilities that were impossible on the fragmented estate. Our phased approach means you start seeing returns on high-value workloads early—not just at the end of a multi-year project.
This is the hardest part of any Fabric migration—and the part most firms underestimate. SSIS packages can't be lifted and shifted into Fabric. They require fundamental re-architecture from procedural ETL to ELT patterns using Fabric Pipelines, Dataflow Gen2, or Spark Notebooks. Each package needs to be assessed for complexity, dependencies, and the optimal Fabric-native replacement. Synapse dedicated SQL pool workloads require DDL refactoring (distribution keys, indexes, and workload management settings don't exist in Fabric Warehouse), data extraction via CETAS to staging, and T-SQL compatibility remediation. Azure Data Factory pipeline migrations need a feature-parity gap assessment since Fabric Data Factory differs from ADF in key ways—no SSIS Integration Runtime, different connection handling, and no datasets concept. Pythian has done this work across complex, multi-workload environments and understands where the hidden compatibility gaps live.
Fabric has matured significantly since its general availability in November 2023. As of mid-2025, over 28,000 paying organizations use it, including 80 percent of the Fortune 500. Microsoft is treating Fabric as its flagship data and analytics platform with monthly feature updates, and is actively steering customers from legacy services—retiring Power BI Premium P-SKUs, feature-freezing Synapse dedicated SQL pools, and migrating ADF users toward Fabric Data Factory. That said, features still move between preview and GA, and capacity-based pricing requires careful management to avoid unexpected costs. This is exactly where Pythian adds value. We know where the sharp edges are—which features are production-ready, which need workarounds, and how to architect around current limitations. We've helped dozens of organizations take Fabric from prototype to production, and we design every implementation with the operational discipline to handle enterprise-scale workloads reliably.
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